Frailty mediates the association between activities of daily living disability and depressive symptoms: a prospective cohort study

doi:10.21203/rs.3.rs-5327030/v1

Download PDF

Research Article

Frailty mediates the association between activities of daily living disability and depressive symptoms: a prospective cohort study

https://doi.org/10.21203/rs.3.rs-5327030/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

Globally, depression is a serious public health problem and it has a high incidence and recurrence rate. The underlying mechanism between the activities of daily living (ADL) disability and depression was not well understood. Our study aimed to explore the mediating role of frailty on the longitudinal association between ADL disability and depressive symptoms.

Methods

This study analyzed data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. A total of 2,245 participants aged ≥45 years old were included. Linear regression, cox regression, and mediation analysis were used to explore the association of ADL disability with development of depressive symptoms and the potential mediating role of frailty.

Results

The results showed that both scores on ADL and frailty were positively associated with the risk of depressive symptoms (P<0.05). No interaction between ADL and covariates on depressive symptoms was found for all subgroups. The association between ADL disability and depressive symptom scores was partially mediated by frailty (mediated proportion = 16.05%) in the Chinese middle-aged and elderly population.

Conclusion

There were positive associations between both scores on ADL and frailty and new-onset depressive symptoms. Individuals with high scores on ADL disability had a higher risk of depressive symptoms, and frailty partially mediated this association.

ADL disability

Depressive Symptoms

Mediating effect

Frailty

CHARLS

Depression is a prevalent mood disorder marked by enduring feelings of sadness, persistent depressed mood, lack of interest, and a sense of worthlessness[1, 2]. These symptoms significantly disrupt psycho-social functioning and diminish the patient's quality of life. The World Health Organization (WHO) estimates[3] that the global prevalence of depression is around 300 million people, and the number is increasing each year. Besides, it is one of the most common mental health disorders in the elderly, affecting about 7% of the elderly[4], and is also a serious economic burden for society in China[5]. Depressive symptoms among older adults in China have been reported to range from 12.8–41.1%, with variations attributed to differences in research populations and sampling regions[6]. Therefore, early screening and intervention during the early stages of depression to identify risk factors for depression would be critical.

Frailty is an age-related clinical syndrome characterized by compromised health, influenced by various factors that stem from the accumulation of health deficits[7, 8]. This condition can lead to a multitude of age-related adverse health outcomes, including issues with mobility, balance, muscle strength, motor processing, cognition, and physical activity[9]. The prevalence of frailty can increase with the age of the population[10], and older people tend to experience more severe frailty[11], which has the potential to place a heavy burden on modern societies with large populations of older individuals. Studies[12, 13] suggested that there is a potential association between frailty and depression in which frailty may increase the risk of developing depression. Furthermore, a systematic review and meta-analysis[14] of results showed that frail individuals had increased odds of developing depression (OR = 4.42, 95% CI 2.66–7.35).

China is currently facing challenges posed by the increasingly aging population and rising prevalence of chronic diseases[15]. Disability, a common occurrence among the elderly, is expected to result in a growing number of disabled elderly individuals in the future. A previous study[16] indicated that the number of disabled elderly individuals in China has already surpassed 40 million, and it is projected to reach 65 million by the year 2030. It is defined as difficulties in the performance of socially defined roles[17]. The activities of daily living (ADL) disability scale is the most widely used measure of disability in daily living, and is composed of basic activities of daily living (BADL) disability and instrumental activities of daily living (IADL) disability[18]. The impairment of ADL disability threatens the lives of older adults. A one-year follow-up study[19] showed a potential association between ADL disability and frailty in middle-aged and older populations, and that ADL domains may improve the prediction of frailty. In addition, previous studies[20, 21] explored the association between ADL disability and depressive symptoms. In summary, multiple studies indicated a significant association between ADL disability and both frailty and depression. However, the relationship between ADL disability, frailty, and depression has not been illustrated. Besides, the majority of studies have examined only extreme degrees of disability, and there has been insufficient research into their specific areas of functioning and varying degrees of disability.

Therefore, leveraging a substantial 7-year prospective cohort encompassing middle-aged and elderly Chinese populations, our study would endeavor to scrutinize the longitudinal association between ADL disability and depression. Additionally, our study would seek to elucidate the potential mediating influence of frailty in delineating this association.

2.1 Study population

The data used in this study were obtained from the follow-up survey of the China Health and Retirement Longitudinal Study (CHARLS) targeting the middle-aged and older population (aged 45 and above). A multi-stage stratified probability proportionate to size sampling technique was used to select participants. The first CHARLS national baseline survey was conducted between June 2011 and March 2012 and involved 17,708 respondents, with a response rate of 80.5%. Follow-up surveys were conducted every 2 to 3 years, and so far, a second (2013), third (2015), fourth (2018), and fifth (2020) wave have been conducted. The details about the design of CHARLS were published elsewhere[22], and it was available through its official website (charls.ccer.edu.cn/en). This study used the baseline data from 2011 and follow-up data from 2013, 2015, and 2018. Participants were excluded if they (1) had depression at baseline; (2) did not participate in the follow-up survey; and (3) were missed anthropometric parameters, basic demographic and chronic disease data at baseline. Then 2,245 of them were included in our analysis (Fig. 1).

2.2 Activities of daily living (ADL) disability

The study used the ADL scale to measure physical function. It was an 11-item scale that assessed participant's BADL and IADL[23]. BADLs comprised six tasks: eating, dressing, bathing, entering or out of bed, toileting, and continence. IADLs consisted of five tasks, including cooking, doing household chores, taking medicine, shopping, and managing money. Each question contained four response options: (1) no difficulty; (2) difficult but achievable; (3) some difficulties and need help; (4) unable to complete. The scores on the 11 items of the ADL scale were summed to give a total, ranging from 11 to 44. The higher ADL score is associated with poorer physical functioning and higher levels of disability. The ADL scale has been employed during investigations in China and internationally, and it has demonstrated high reliability and validity[24].

2.3 Depressive symptoms

The modified Center for Epidemiologic Studies Depression Scale (CES-D-10) excluding two items used for identifying exhaustion (a frailty component) was used to screen for the presence of depressive symptoms[25, 26]. It exhibited adequate reliability and validity when it was used to assess depression among Chinese elderly individuals living in the community. Each item with four answers, as follows: "rarely (< 1 day/week) "; "some days (1–2 days per week) "; "occasionally (3–4 days) "; "Mostly (5–7 days a week) ". Negative items "rarely", "some days", "occasionally", and "mostly" were scored as 0, 1, 2, and 3 points, respectively. Conversely, positive items were scored as 3, 2, 1, and 0 points for the same descriptors. The total is obtained by adding the scores of the eight items of the CES-D-10, ranging from 0 to 24. Participants with a total score of 12 or higher were considered depressed[27].

2.4 Frailty

Frailty was measured by the physical frailty phenotype (PFP)[28], which includes five operational components: slowness, weakness, low physical activity, exhaustion, and weight loss. Slowness was defined as falling within the slowest 20% of the population distribution in terms of the time taken to walk a 2.5-meter course, adjusting for sex and height. The specific criteria for defining slowness based on sex and height were determined from previous research utilizing the CHARLS data[26]. Weakness was identified as a maximum handgrip strength that fell below 20% of the population distribution, adjusting for sex and body mass index (BMI). The criteria for defining weakness based on sex and BMI were also established from prior research[26]. Participants met the criteria for low physical activity if they did not walk 10 or more minutes continuously during a typical week. Exhaustion was characterized by two questions from the CES-D-10. Two questions were “I could not get going” and “I felt everything I did was an effort”. Consistent with the scores assigned to the scale above, participants met the criteria for exhaustion if they scored more than 3 on two questions. Weight loss was identified as self-reporting loss of ≥ 5 kilograms (kg) in the last year or having a BMI ≤ 18.5 kg/m². Based on the literature[29, 30], we included respondents who provided data on at least four of the constituent frailty components to retain a larger sample size. A score of 1 was assigned to those who matched its components, otherwise a score of 0. The total score for frailty ranged from 0 to 5, with higher scores representing higher levels of frailty.

2.5 Covariates

The covariates included socio-demographic characteristics and health-related factors assessed at baseline. Socio-demographic variables included age, sex (male and female), hukou (Hukou, a term originating centuries ago in China, refers to the national household registration that Chinese governments have historically used to try to fix the population in place geographically) status (rural and urban), marital status (married and others), education level (illiterate, primary school and below, and junior high school or above). Health-related factors included self-reported smoking, drinking, and chronic disease status. Smoking status was categorized as never, former, and current. Drinking status was categorized into three groups: more than once a month, less than once a month, and do not drink. Chronic diseases include hypertension, diabetes, heart disease, stroke, renal disease, arthritis, tuberculosis, and respiratory and liver diseases. Participants’ chronic disease status was assessed by self-report and categorized according to the number of chronic diseases (0, 1, ≥ 2).

2.6 Statistical Analysis

Descriptive statistic methods were used to analyze the characteristics of the study subjects. Means (standard errors) were used to describe continuous variables and comparisons were made using Student’s t-test, frequencies (percentages) were used to describe categorical variables and comparisons were made using chi-square tests. Cox proportional hazard regression models were used to calculate hazard ratios (HRs) and their 95% confidence intervals (CIs) for the associations of ADL disability and frailty with the risk of depressive symptoms. Model II was adjusted for age, sex, and hukou status. Model III was adjusted for variables in model II plus education level, marital status, smoking, drinking, and chronic disease. Model IV further adjusted for frailty based on model III. A stratified analysis was used to conduct a sensitivity analysis of the Cox regression, and P-interaction between ADL and each stratified variable was also tested. We assessed the mediating effect of frailty indicators on the association between ADL disability and depressive symptoms using the mediation package in R[31], The indirect, direct, and total effects of each mediator were calculated by integrating mediation and outcome models while adjusting for all covariates in model III. The specific steps of the mediation analysis involved: (1) determining the total effect of ADL disability on depressive symptoms; (2) examining the effect of ADL disability on frailty; and (3) evaluating both the direct effect of ADL disability on depressive symptoms and the indirect effect of frailty on this association. The formula for calculating the proportion of intermediaries was indirect effect / (indirect effect + direct effect) × 100%. All statistical analyses were conducted by IBM SPSS 24.0 and R version 4.1.2. Besides, two-sided P < 0.05 was set as the threshold for statistical significance.

3.1 Baseline Characteristics of Study Participants

The current study included 2,245 participants in the final analysis based on inclusion and exclusion criteria, of whom 701 developed depressive symptoms. Table 1 showed the characteristics of the study population according to the presence or absence of depressive symptoms at follow-up. The average age of the whole cohort was 57.49 years old, and 44.23% of them were male. In comparison to the without depressive symptoms, depressed participants were more likely to be female, in rural households, had lower education levels, smoked and drank less, had a higher proportion of chronic diseases, had higher levels of ADL, BADL, IADL, and frailty (P < 0.05).

Table 1

Comparison of sample characteristics between depressive symptoms and non- depressive symptoms (n = 2,245).
	Overall (n = 2,245)	Depressive symptoms (n = 701)	Non- depressive symptoms (n = 1,544)	χ²/t	P
Age(year)	57.49(0.17)	57.27(0.30)	57.58(0.21)	0.848	0.076
ADL	11.73(0.04)	12.00(0.08)	11.61(0.04)	4.545	< 0.001
BADL	6.26(0.02)	6.35(0.04)	6.22(0.02)	3.400	< 0.001
IADL	5.47(0.03)	5.64(0.06)	5.39(0.03)	4.166	< 0.001
Frailty	0.35(0.01)	0.43(0.02)	0.32(0.01)	4.282	< 0.001
Sex				51.242	< 0.001
Male	993(44.23)	232(33.10)	761(49.29)
Female	1252(55.77)	469(66.90)	783(50.71)
Hukou status				19.215	< 0.001
Rural	1820(81.07)	606(86.45)	1214(78.63)
Urban	425(18.93)	95(13.55)	330(21.37)
Education level				40.767	< 0.001
Illiterate	483(21.51)	198(28.25)	285(18.46)
Primary school and below	951(42.36)	307(43.79)	644(41.71)
Junior high school or above	811(36.13)	196(27.96)	615(39.83)
Marital status				1.282	0.257
Married	2077(92.52)	642(91.58)	1435(92.94)
Others	168(7.48)	59(8.42)	109(7.06)
Smoking				17.375	< 0.001
Never	1405(62.58)	480(68.47)	925(59.91)
Former	196(8.73)	43(6.13)	153(9.91)
Current	644(28.69)	178(25.39)	466(30.18)
Drinking				23.306	< 0.001
More than once a month	515(22.94)	118(16.83)	397(25.71)
Less than once a month	165(7.35)	48(6.85)	117(7.58)
Do not drink	1565(69.71)	535(76.32)	1030(66.71)
Chronic disease				22.331	< 0.001
0	698(31.09)	173(24.68)	525(34.00)
1	674(30.02)	215(30.67)	449(29.73)
≥ 2	873(38.89)	313(44.65)	560(36.27)
Abbreviations: ADL, activities of daily living, BADL, basic activities of daily living, IADL, instrumental activities of daily living. Continuous variables were expressed with means (standard error) and categorical variables were described with frequencies (percentages). Continuous variables were compared using t-test and categorical variables were using chi-square tests. P < 0.05 was set as the threshold of statistical significance and marked in bold values.

3.2 Association between ADL disability, frailty and depressive symptoms

Table 2 showed the association between ADL disability and depressive symptoms. We found that ADL, and its components BADL and IADL, were positively associated with the risk of depressive symptoms in three models (Model I, Model II, and Model III). In the fully adjusted model (Model III), the HRs of ADL, BADL, and IADL were 1.07(1.04, 1.11), 1.12(1.04, 1.21), and 1.10(1.04, 1.15), respectively (P < 0.05). Similarly, there were significant positive associations found between high levels of frailty with the risk of depressive symptoms (P < 0.05). When the model adjusted for frailty (Model IV), the association between ADL (included BADL and IADL) and depressive symptoms became smaller (P < 0.05).

Table 2

Cox proportional hazard models for the association between ADL disability and depressive symptoms.
	Model I		Model II		Model III			Model IV
	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)		P	HR (95% CI)	P
ADL	1.08(1.04, 1.11)	< 0.001	1.08(1.05, 1.12)	< 0.001	1.07(1.04, 1.11)	< 0.001		1.06(1.03, 1.10)	< 0.001
BADL	1.12(1.05, 1.20)	< 0.001	1.14(1.06, 1.22)	< 0.001	1.12(1.04, 1.21)	0.002		1.10(1.02, 1.18)	0.012
IADL	1.11(1.06, 1.16)	< 0.001	1.11(1.06, 1.17)	< 0.001	1.10(1.04, 1.15)	< 0.001		1.08(1.03, 1.13)	0.002
Frailty	1.28(1.15,1.44)	< 0.001	1.32(1.17, 1.48)	< 0.001	1.29(1.14, 1.45)	< 0.001		-	-
Abbreviations: ADL, activities of daily living, BADL, basic activities of daily living, IADL, instrumental activities of daily living.
Model I = unadjusted model
Model II = Model I + age + sex + hukou status
Model III = Model II + education level + marital status + smoking + drinking + chronic disease
Model IV = Model III + frailty

3.3 Subgroup analyses

Subgroup analysis and interaction tests by sex, hukou status, education level, marital status, smoking, drinking, and chronic disease were conducted to assess whether the association between ADL disability and depressive symptoms was consistent across the general population. As shown in Fig. 2, none of the subgroups had statistically significant interactions, the association between ADL disability and depressive symptoms remained robust in all subgroups.

3.4 Mediation analysis

Then, we explored the mediation effect of frailty on the association between ADL disability and depressive symptoms, as shown in Fig. 3. First, controlling for all covariates, a linear regression analysis was performed with ADL disability, and its components BADL and IADL, as independent variables and frailty as the dependent variable. The results showed that ADL, BADL, and IADL were positively associated with frailty (P < 0.05) (Table S1). Second, the Cox regression analysis was performed with frailty as the independent variable and the incidence of depressive symptoms as the dependent variable. The results showed that with the increase in frailty, the risk of depressive symptoms increased (P < 0.05), as shown in Table S2.

The mediation analysis found that high scores on ADL might contribute to depression by influencing frailty (P < 0.05). Frailty partly mediated the association between ADL disability and depressive symptoms, with a percentage of 16.05% (IE, 0.160; 95% CI, 0.080–0.273). Similarly, the mediating role of frailty was found in the association between BADL, IADL, and depressive symptoms (e.g., Figure S1 and Figure S2), respectively, with mediating proportions of 19.84%, 14.21%.

To the best of our knowledge, this is the first large prospective cohort study to explore the potential relationship between ADL disability, frailty, and depression in the middle-aged and elderly Chinese population based on CHARLS. Overall, we found that a positive association between ADL (including BADL and IADL) disability and the risk of depressive symptoms existed, and that frailty was associated with increased risk of depressive symptoms. Furthermore, the association was partially mediated through frailty. Besides, the results of the sensitivity analyses showed no interaction between ADL disability and the stratification variables, and the results were robust.

Previous studies explored an association between ADL disability and depression, but results remained controversial. A cross-sectional study of Chinese older adults[32] showed that the association between ADL disability and depression was significant in both urban and rural older adults. In Chinese middle-aged and older adults, ADL disability was associated not only with an increased risk of depressive symptoms in themselves but even in spouses without ADL disability[33]. However, the study by Barry et al. pointed to no significant association between older adults with depression and ADL functioning[34]. In addition, previous studies have been inconsistent in their identification of a causal relationship between ADL disability and depression[35–37]. Therefore, we demonstrated the causal association between ADL disability and the onset of depressive symptoms in the prospective cohort study.

The results of our study confirmed that ADL disability is positively associated with an increased incidence of depressive symptoms, with higher ADL scores being associated with a higher incidence of depressive symptoms. Physical functioning is known to decline with age. Physical decline is a key challenge to the ability of older adults to care for themselves, and it is difficult to perform many daily activities independently as physical functioning declines[38]. ADL is essential to maintaining independence in older adults. Therefore, the direct mechanism by which ADL disability leads to an increased incidence of depressive symptoms may be due to the negative experiences caused by the inability to perform activities of daily living[39]. As a result of their reduced physical condition, subjects with lower levels of ADL scores are unable to independently perform one or more activities of daily living, which can directly lead to a reduced quality of life and thus more feelings of depression. The indirect effect of ADL disability on depressive symptoms may be due to psychological stress triggered by limitations in one's mobility. Low and declining ability to perform ADLs may constitute a significant stressor for elderly individuals. The limitations in daily activities and physical functioning can lead to a loss of independence and dependence on others for ADLs which may result in lower self-esteem, loss of self-control, and impaired personal and professional fulfillment for these individuals[39, 40]. This psychological distress caused by limitations in outside activities, such as feelings of loss, frustration with slow recovery, and the inability to cope with dependency, can greatly affect the lives of older adults and lead to depressive symptoms and sadness[41]. In addition, studies have shown that elderly individuals who have lost their independence are at higher risk of social isolation and have higher rates of morbidity and mortality[34, 42, 43]. Depression is therefore to be expected.

The association between ADL disability, frailty, and depression has been analyzed in previous studies[44, 45], with a higher prevalence of ADL disability and frailty observed in depressed patients, both of which are risk factors for depression. Studies have also explored the associations between ADL disability and depression, ADL disability and frailty[46], and frailty and depression[47], respectively. There is a correlation between all three and that frailty may play an important role in the pathway linking the two. For the first time, our study extended previous research and evaluated the possible mediating role of frailty between ADL disability and depression. We found that frailty significantly mediated the association between ADL disability and the onset of depressive symptoms. High scores on ADLs caused high levels of frailty, which increased the risk of depressive symptoms.

In both aging research and practice, frailty is a key concept and a strong predictor of a range of health problems. We showed that ADL disability was significantly associated with frailty. The result was in line with existing knowledge that ADL is important influencing factor of frailty[48]. This implies that hypoactive somatic functions contribute to the onset and development of frailty. Somatic function reflects the strength and functional status of muscles throughout the body, which is closely related to sarcopenia and is an integral part of the somatic component of frailty[49]. In addition, reduced somatic function has been associated with several comorbidities, and cognitive deficits, which exacerbate the progression of frailty[50]. A positive association between frailty and depressive symptoms was also noted in our study, which is consistent with previous findings. A meta-analysis noted that compared to non-frail individuals, frail individuals had increased odds of depression (OR = 4.42,95% CI 2.66–7.35) and that frailty increased the risk of depression[14]. As a syndrome common to older adults, frailty is affected by a variety of factors, such as pain, mobility and balance problems, and poor endurance[51]. All of these factors can lead to a poorer sense of experiencing life, which can lead to depression. Depression may also be caused by a state of frailty due to reduced gait speed and physical activity, or by an increase in sedentary behavior, risk of falls, weight loss, and malnutrition, causing the persistence of their typical emotional symptoms, including sadness, lack of pleasure and helplessness[52]. In addition, there may be common pathophysiological pathways between depression and frailty, such as cerebrovascular disease and chronic inflammation. Subclinical vascular disease that causes high signals in prefrontal white matter in patients with late-life depression has long been considered a key factor in the prevalence of frailty[53]. A growing body of evidence also supports a positive correlation between inflammatory cytokines and frailty[54], such as interleukin 6 (IL 6) and C-reactive protein, which are associated with decreased muscle mass and strength. These two inflammatory factors, in turn, are elevated in patients with late-life depression, negatively affecting central dopaminergic function, which may contribute to fatigue and depressed mood[55, 56]. Thus, inflammation may be one of the common pathogenic mechanisms of depression and frailty.

This study had some advantages. First, this is a prospective study with long-term follow-up in the middle-aged and elderly Chinese population based on the CHARLS database, which was representative of the health status of the Chinese population. Second, our research's most significant advantage is that it's the first mediation study to evaluate how frailty affects the relationship between ADL disability and depressive symptoms. The results may be useful in creating focused intervention plans to treat and prevent depression. However, there are still some limitations. Firstly, the CES-D-10 was employed to assess the number of self-reported depressions in the previous week, which might introduce recollection bias. Secondly, all missing values were excluded, which may have reduced the representativeness of the sample. Future studies would require further analysis of the effect of the ADL disability and frailty on depression.

There were positive associations between both scores on the ADL and frailty and new-onset depressive symptoms in middle-aged and elderly population. Individuals with high scores on ADL disability had a higher risk of depressive symptoms, and frailty partially mediated this association. Further large prospective studies are needed to investigate the effects of ADL disability and frailty on depressive symptoms, and it is important to clarify the pathophysiological mechanisms for the prevention of depression.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Clinical trial number: Not applicable.

Ethics approval and consent to participate: Not applicable. The manuscript does not report on or involve the use of any animal or human tissue, and all data are from the dataset and kept anonymous. The Second Hospital of Jilin University ethics committee waived this ethics approval because this is unnecessary based on regulations.

Funding: Not applicable.

Acknowledgements

The authors thank the staff and participants of the China Health and Retirement Longitudinal Study (CHARLS).

Authors’ Contributions

Conceptualization: Guangping Meng, Dongyi Zhang, and Yan Liu.

Data curation: Dongyi Zhang, and Jinying Wei.

Software: Dongyi Zhang.

Formal Analysis: Dongyi Zhang.

Visualization: Jinying Wei.

Supervision: Guangping Meng.

Investigation: Xiuqin Xin, and Ying Zhu.

Methodology: Guangping Meng, and Dongyi Zhang.

Writing – original draft: Dongyi Zhang.

Writing – review & editing: Dongyi Zhang, Shufei Li, Hongyue Chen, and Guangping Meng.

All authors agreed with the final manuscript.

McCarron RM, Shapiro B, Rawles J, Luo J: Depression. Ann Intern Med 2021, 174(5):Itc65-itc80.
Eurelings LS, van Dalen JW, Ter Riet G, Moll van Charante EP, Richard E, van Gool WA, Almeida OP, Alexandre TS, Baune BT, Bickel H et al: Apathy and depressive symptoms in older people and incident myocardial infarction, stroke, and mortality: a systematic review and meta-analysis of individual participant data. Clin Epidemiol 2018, 10:363-379.
Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet 2021, 398(10312):1700-1712.
Whiteford HA, Ferrari AJ, Degenhardt L, Feigin V, Vos T: The global burden of mental, neurological and substance use disorders: an analysis from the Global Burden of Disease Study 2010. PLoS One 2015, 10(2):e0116820.
Zhou X, Li J, Gu W, Wang J, Zhu Y, Zhang G, Ding Y, Tang Y: Prevalence and associated factors of anxiety and depression among patients with chronic respiratory diseases in eight general hospitals in Jiangsu Province of China: A cross-sectional study. Psychiatry Res 2017, 251:48-53.
Li N, Pang L, Chen G, Song X, Zhang J, Zheng X: Risk factors for depression in older adults in Beijing. Can J Psychiatry 2011, 56(8):466-473.
Hubbard RE, Theou O: Frailty: enhancing the known knowns. Age Ageing 2012, 41(5):574-575.
Lorenzo-López L, Maseda A, de Labra C, Regueiro-Folgueira L, Rodríguez-Villamil JL, Millán-Calenti JC: Nutritional determinants of frailty in older adults: A systematic review. BMC Geriatr 2017, 17(1):108.
Gobbens RJ, Luijkx KG, Wijnen-Sponselee MT, Schols JM: Toward a conceptual definition of frail community dwelling older people. Nurs Outlook 2010, 58(2):76-86.
Jayanama K, Theou O, Blodgett JM, Cahill L, Rockwood K: Frailty, nutrition-related parameters, and mortality across the adult age spectrum. BMC Med 2018, 16(1):188.
Chen LY, Fang TJ, Lin YC, Hsieh HF: Exploring the Mediating Effects of Cognitive Function, Social Support, Activities of Daily Living and Depression in the Relationship between Age and Frailty among Community-Dwelling Elderly. Int J Environ Res Public Health 2021, 18(23).
Luo X, Ruan Z, Liu L: Causal relationship between depression and aging: a bidirectional two-sample Mendelian randomization study. Aging Clin Exp Res 2023, 35(12):3179-3187.
Nerobkova N, Park YS, Park EC, Shin J: Frailty transition and depression among community-dwelling older adults: the Korean Longitudinal Study of Aging (2006-2020). BMC Geriatr 2023, 23(1):148.
Soysal P, Veronese N, Thompson T, Kahl KG, Fernandes BS, Prina AM, Solmi M, Schofield P, Koyanagi A, Tseng PT et al: Relationship between depression and frailty in older adults: A systematic review and meta-analysis. Ageing Res Rev 2017, 36:78-87.
Pan C, Kelifa MO, Liang J, Wang P: Joint trajectories of disability and related factors among older adults in China. Public Health 2021, 199:96-102.
Zheng X, Pang L, Chen G, Huang C, Liu L, Zhang L: Challenge of Population Aging on Health. In: Public Health Challenges in Contemporary China: An Interdisciplinary Perspective. edn. Edited by Islam MDN. Berlin, Heidelberg: Springer Berlin Heidelberg; 2016: 43-53.
Wolf DA, Freedman VA, Ondrich JI, Seplaki CL, Spillman BC: Disability Trajectories at the End of Life: A "Countdown" Model. J Gerontol B Psychol Sci Soc Sci 2015, 70(5):745-752.
Ng TP, Niti M, Chiam PC, Kua EH: Physical and cognitive domains of the Instrumental Activities of Daily Living: validation in a multiethnic population of Asian older adults. J Gerontol A Biol Sci Med Sci 2006, 61(7):726-735.
Hiriscau EI, Buzdugan EC, Hui LA, Bodolea C: Exploring the Relationship between Frailty, Functional Status, Polypharmacy, and Quality of Life in Elderly and Middle-Aged Patients with Cardiovascular Diseases: A One-Year Follow-Up Study. Int J Environ Res Public Health 2022, 19(4).
Jiang J, Tang Z, Futatsuka M: The impact of ADL disability on depression symptoms in a community of Beijing elderly, China. Environ Health Prev Med 2002, 7(5):199-204.
Chen CM, Mullan J, Su YY, Griffiths D, Kreis IA, Chiu HC: The longitudinal relationship between depressive symptoms and disability for older adults: a population-based study. J Gerontol A Biol Sci Med Sci 2012, 67(10):1059-1067.
Zhao Y, Hu Y, Smith JP, Strauss J, Yang G: Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol 2014, 43(1):61-68.
Jin X, He J, Liang Y, Sun X, Yan S, Wu Y, Li Y, Mei L, Song J, Pan R et al: Associations between household solid fuel use and activities of daily living trajectories: A nationwide longitudinal study of middle and older adults in China. Environ Int 2022, 170:107605.
Dai S, Wang S, Jiang S, Wang D, Dai C: Bidirectional association between handgrip strength and ADLs disability: a prospective cohort study. Front Public Health 2023, 11:1200821.
Andresen EM, Malmgren JA, Carter WB, Patrick DL: Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale). Am J Prev Med 1994, 10(2):77-84.
Wu C, Smit E, Xue QL, Odden MC: Prevalence and Correlates of Frailty Among Community-Dwelling Chinese Older Adults: The China Health and Retirement Longitudinal Study. J Gerontol A Biol Sci Med Sci 2017, 73(1):102-108.
Cheng ST, Chan AC: The Center for Epidemiologic Studies Depression Scale in older Chinese: thresholds for long and short forms. Int J Geriatr Psychiatry 2005, 20(5):465-470.
Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G et al: Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001, 56(3):M146-156.
Liu H, Li D, Zhao X, Fang B, Zhang Q, Li T: Longitudinal Impact of Frailty States and Sleep Duration on Subsequent Depressive Symptoms of Older Adults. J Am Geriatr Soc 2021, 69(4):1003-1011.
Zhao X, Li D, Zhang Q, Liu H: Spousal concordance in frailty predicting mental and functional health decline: A four-year follow-up study of older couples in urban and rural China. J Clin Nurs 2022, 31(5-6):679-688.
Geng T, Zhu K, Lu Q, Wan Z, Chen X, Liu L, Pan A, Liu G: Healthy lifestyle behaviors, mediating biomarkers, and risk of microvascular complications among individuals with type 2 diabetes: A cohort study. PLoS Med 2023, 20(1):e1004135.
Yan Y, Du Y, Li X, Ping W, Chang Y: Physical function, ADL, and depressive symptoms in Chinese elderly: Evidence from the CHARLS. Front Public Health 2023, 11:1017689.
Fan X, Guo X, Ren Z, Li X, He M, Shi H, Zha S, Qiao S, Zhao H, Li Y et al: The prevalence of depressive symptoms and associated factors in middle-aged and elderly Chinese people. J Affect Disord 2021, 293:222-228.
Barry LC, Murphy TE, Gill TM: Depression and functional recovery after a disabling hospitalization in older persons. J Am Geriatr Soc 2011, 59(7):1320-1325.
Wu C: The mediating and moderating effects of depressive symptoms on the prospective association between cognitive function and activities of daily living disability in older adults. Arch Gerontol Geriatr 2021, 96:104480.
Scher C, Nepomnyaschy L, Amano T: Comparison of Cognitive and Physical Decline as Predictors of Depression Among Older Adults. J Appl Gerontol 2023, 42(3):387-398.
Pai M, Muhammad T: Subjective social status and functional and mobility impairments among older adults: life satisfaction and depression as mediators and moderators. BMC Geriatr 2023, 23(1):685.
Muramatsu N, Yin H, Hedeker D: Functional declines, social support, and mental health in the elderly: does living in a state supportive of home and community-based services make a difference? Soc Sci Med 2010, 70(7):1050-1058.
Li J, Yang L, Lv R, Kuang J, Zhou K, Xu M: Mediating effect of post-stroke depression between activities of daily living and health-related quality of life: meta-analytic structural equation modeling. Qual Life Res 2023, 32(2):331-338.
Byeon H, Koh HW: The relationship between communication activities of daily living and quality of life among the elderly suffering from stroke. J Phys Ther Sci 2016, 28(5):1450-1453.
Žikić TR, Divjak I, Jovićević M, Semnic M, Slankamenac P, Žarkov M, Žikić M: The effect of post stroke depression on functional outcome and quality of life. Acta Clin Croat 2014, 53(3):294-301.
Quadri P, Tettamanti M, Bernasconi S, Trento F, Loew F: Lower limb function as predictor of falls and loss of mobility with social repercussions one year after discharge among elderly inpatients. Aging Clin Exp Res 2005, 17(2):82-89.
Keeler E, Guralnik JM, Tian H, Wallace RB, Reuben DB: The impact of functional status on life expectancy in older persons. J Gerontol A Biol Sci Med Sci 2010, 65(7):727-733.
Liu A, Peng Y, Zhu W, Zhang Y, Ge S, Zhou Y, Zhang K, Wang Z, He P: Analysis of Factors Associated With Depression in Community-Dwelling Older Adults in Wuhan, China. Front Aging Neurosci 2021, 13:743193.
Wang Q, Song D, Lin Q, Tao A, Zhang Y, Li X, Qiu X: The critical role of physical frailty and function on depressive symptoms among community-dwelling older adults in China: A cross-sectional study. Front Psychiatry 2023, 14:1134427.
Yuan Y, Lin S, Huang X, Li N, Zheng J, Huang F, Zhu P: The identification and prediction of frailty based on Bayesian network analysis in a community-dwelling older population. BMC Geriatr 2022, 22(1):847.
Sang N, Liu RC, Zhang MH, Lu ZX, Wu ZG, Zhang MY, Li BH, Wei M, Pan HF, Wu GC: Changes in frailty and depressive symptoms among middle-aged and older Chinese people: a nationwide cohort study. BMC Public Health 2024, 24(1):301.
Merchant RA, Chen MZ, Tan LWL, Lim MY, Ho HK, van Dam RM: Singapore Healthy Older People Everyday (HOPE) Study: Prevalence of Frailty and Associated Factors in Older Adults. J Am Med Dir Assoc 2017, 18(8):734.e739-734.e714.
Sieber CC: Malnutrition and sarcopenia. Aging Clin Exp Res 2019, 31(6):793-798.
Yang F, Gu D: Predictability of frailty index and its components on mortality in older adults in China. BMC Geriatr 2016, 16:145.
Woods NF, LaCroix AZ, Gray SL, Aragaki A, Cochrane BB, Brunner RL, Masaki K, Murray A, Newman AB: Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study. J Am Geriatr Soc 2005, 53(8):1321-1330.
Hajek A, Brettschneider C, Posselt T, Lange C, Mamone S, Wiese B, Weyerer S, Werle J, Fuchs A, Pentzek M et al: Predictors of Frailty in Old Age - Results of a Longitudinal Study. J Nutr Health Aging 2016, 20(9):952-957.
Hare DL, Toukhsati SR, Johansson P, Jaarsma T: Depression and cardiovascular disease: a clinical review. Eur Heart J 2014, 35(21):1365-1372.
Soysal P, Stubbs B, Lucato P, Luchini C, Solmi M, Peluso R, Sergi G, Isik AT, Manzato E, Maggi S et al: Inflammation and frailty in the elderly: A systematic review and meta-analysis. Ageing Res Rev 2016, 31:1-8.
Vaughan L, Corbin AL, Goveas JS: Depression and frailty in later life: a systematic review. Clin Interv Aging 2015, 10:1947-1958.
Brown PJ, Rutherford BR, Yaffe K, Tandler JM, Ray JL, Pott E, Chung S, Roose SP: The Depressed Frail Phenotype: The Clinical Manifestation of Increased Biological Aging. Am J Geriatr Psychiatry 2016, 24(11):1084-1094.

No competing interests reported.

Supplementarymaterials.docx
Supplementary Materials Table S1 Multivariable-adjusted linear regression models for the association between ADL disability and frailty. Table S2 Cox proportional hazard models for the association between frailty and depressive symptoms. Figure S1 Mediation analysis of frailty on the association between BADL and depressive symptoms. Figure S2 Mediation analysis of frailty on the association between IADL and depressive symptoms.

Download PDF

Version 1

posted

You are reading this latest preprint version

Frailty mediates the association between activities of daily living disability and depressive symptoms: a prospective cohort study

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methods

2.1 Study population

2.2 Activities of daily living (ADL) disability

2.3 Depressive symptoms

2.4 Frailty

2.5 Covariates

2.6 Statistical Analysis

3. Results

3.1 Baseline Characteristics of Study Participants

3.2 Association between ADL disability, frailty and depressive symptoms

3.3 Subgroup analyses

3.4 Mediation analysis

4. Discussion

5. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1